Triple
T27151987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troutman |
E682413
|
entity |
| Predicate | hasHighSchoolNearby |
P6776
|
FINISHED |
| Object | South Iredell High School |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: South Iredell High School | Statement: [Troutman, hasHighSchoolNearby, South Iredell High School]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighSchoolNearby Context triple: [Troutman, hasHighSchoolNearby, South Iredell High School]
-
A.
hasNearbyInstitution
chosen
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
B.
hasSchoolIn
Indicates that a school is located within or operates in a specified place or region.
-
C.
attendedHighSchoolIn
Indicates that an entity completed or was enrolled in high school education in a specified location.
-
D.
hasNearbyInstitutionType
Indicates that an entity has at least one institution of a specified type located in its nearby geographic vicinity.
-
E.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: April 27, 2026, 9:14 a.m.